IMAGE FUSION USING CURVELET TRANSFORM

Abstract

Image fusion is the process by which two or more images are combined into a single image retaining the important features from each of the original images. The fusion of images is often required for images acquired from different modalities or capture techniques of the same scene or objects. The fusion of high-spectral but low-spatial resolution multispectral satellite images and low- spectral but high-spatial resolution panchromatic satellite images is a very useful technique in various applications of remote sensing. Recently, some studies showed that a wavelet-based image fusion method provides high quality spectral content in fused images. However, most wavelet-based methods yield fused results with spatial resolution that is less than that obtained via the Brovey, IHS, and PCA fusion methods. Edges play a fundamental role in image representation, one effective means to enhance spatial resolution is to enhance the edges. In this thesis, a new image fusion method based on a curvelet transform is introduced, which represents edges better than wavelets. The curvelet-based image fusion method provides richer information in the spatial and spectral domains simultaneously. Here Quick Bird image fusion is performed and found that the proposed method provides optimum fusion results.